

In [2]:

    
import cv2
import matplotlib.pyplot as plt
import time
import cProfile
import numpy as np

Walker detection with openCV

Open video and get video info



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video_capture = cv2.VideoCapture('resources/TestWalker.mp4')



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# From https://www.learnopencv.com/how-to-find-frame-rate-or-frames-per-second-fps-in-opencv-python-cpp/
# Find OpenCV version
(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
print major_ver, minor_ver, subminor_ver

# With webcam get(CV_CAP_PROP_FPS) does not work.
# Let's see for ourselves.

if int(major_ver)  < 3 :
    fps = video_capture.get(cv2.cv.CV_CAP_PROP_FPS)
    print "Frames per second using video.get(cv2.cv.CV_CAP_PROP_FPS): {0}".format(fps)
else :
    fps = video_capture.get(cv2.CAP_PROP_FPS)
    print "Frames per second using video.get(cv2.CAP_PROP_FPS) : {0}".format(fps)


# Number of frames to capture
num_frames = 120;


print "Capturing {0} frames".format(num_frames)

# Start time
start = time.time()

# Grab a few frames
for i in xrange(0, num_frames) :
    ret, frame = video_capture.read()


# End time
end = time.time()

# Time elapsed
seconds = end - start
print "Time taken : {0} seconds".format(seconds)

# Calculate frames per second
fps  = num_frames / seconds;
print "Estimated frames per second : {0}".format(fps);









    



2 4 8
Frames per second using video.get(cv2.cv.CV_CAP_PROP_FPS): 20.8333333333
Capturing 120 frames
Time taken : 13.8059420586 seconds
Estimated frames per second : 8.69190957712



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# cProfile.runctx('video_capture.read()', globals(), locals(), 'profile.prof')
# use snakeviz to read the output of the profiling

Track walker using difference between frames

Following http://www.codeproject.com/Articles/10248/Motion-Detection-Algorithms



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def getSmallGrayFrame(video):
    ret, frame = video.read()
    if not ret:
        return ret, frame
    frameSmall = frame[::4, ::-4]
    gray = cv2.cvtColor(frameSmall, cv2.COLOR_BGR2GRAY)
    return ret, gray



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#cv2.startWindowThread()
count = 0
for x in range(200):
    count = count + 1
    print count
    ret1, gray1 = getSmallGrayFrame(video_capture)
    ret2, gray2 = getSmallGrayFrame(video_capture)
    diff = cv2.absdiff(gray1, gray2)
    print np.amax(diff), np.amin(diff)
    print 
    diffThresh = cv2.threshold(diff, 15, 255, cv2.THRESH_BINARY)
    
    kernel = np.ones((3,3),np.uint8)
    erosion = cv2.erode(diffThresh[1],kernel,iterations = 1)
    dilation = cv2.dilate(erosion,kernel,iterations = 1)
    
    color1 = cv2.cvtColor(gray1, cv2.COLOR_GRAY2RGB)
    color1[:,:,0:1] = color1[:,:,0:1]
    
    colorDil = cv2.cvtColor(dilation, cv2.COLOR_GRAY2RGB)
    colorDil[:,:,1:2] = colorDil[:,:,1:2]*0
    
    total = cv2.add(color1, colorDil)
    if not ret1 or not ret2:
        break
    cv2.imshow('Video', total)
    cv2.imwrite('resources/frame{}.png'.format(x), total)
    if cv2.waitKey(1) & 0xFF == ord('q'):  # Need the cv2.waitKey to update plot
        break



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# To close the windows: http://stackoverflow.com/questions/6116564/destroywindow-does-not-close-window-on-mac-using-python-and-opencv#15058451
cv2.waitKey(1000)

cv2.waitKey(1)
cv2.destroyAllWindows()
cv2.waitKey(1)









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-1



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